A Framework of GRID Problem-Solving Environment Employing Robust Evolutionary Search

This paper presents a problem-solving framework based on robust evolutionary search in GRID computing environment. Our problem-solving environment called virtual innovative laboratory performs simulator programs in parallel and optimize their input parameters employing a competent evolutionary algorithm with gene analysis. The objective of our project is to replace a part of human designer's try-and-error processes by a parallel and robust evolutionary search on GRID computing systems.